Microorganisms are the most ancient, the most abundant, and the most diverse life form on
Earth. Over billions of years, their metabolic activity, coupled with geophysical
processes, has been shaping Earth's surface chemistry (1). Today, microorganisms catalyze the bulk of
biochemical fluxes in virtually every ecosystem, including the ocean, soil, and the
human gut.

Unraveling the principles by which microbial communities couple with physical processes
to give rise to biogeochemical fluxes is of central importance to ecology, environmental
sciences, industry, and human health. Yet, our understanding of microbial communities
and their role in ecosystems remains extremely limited, partly because the enormous
microbial diversity poses a serious challenge to conceptual and mathematical
modeling.

The Pathway-Centric Paradigm

Despite the millions of extant microbial species, most elemental fluxes are driven by
a core set of energy-transducing metabolic pathways, encoded by a few genes. Over
time, these genes have evolved to use various energy sources, such as light for
photosynthesis or various chemical compounds for respiration, and have propagated
within a multitude of microbial taxa (1).

The growth of microorganisms (and, thus, of genes) is inevitably tied to the activity
of these genes, which in turn is strongly constrained by current environmental
conditions. It is therefore tempting to theorize that energy-transducing
pathways—or more precisely, the genes encoding them—may behave as
independent units of replication and selection (2) and that environmental conditions prescribe the
overall biochemical fluxes catalyzed by these genes, regardless of the precise
species involved. Such a “pathway-centric” paradigm, if applicable,
would greatly simplify the modeling of microbial processes at ecosystem scales.

Sequencing the Bromeliad Microbiome

As part of my graduate work, I developed and tested the applicability of this
paradigm to a multitude of environments, using experiments, DNA sequencing, and
mathematical modeling. A key prediction of the pathway-centric paradigm is that
similar environments will promote the growth and activity of similar
energy-transducing pathways, even if the species encoding each pathway varied. To
test this prediction, I examined microbial communities within the foliage of
multiple bromeliad plants (3,
4).

Bromeliads are popular model systems for ecology because their cavity-shaped foliage
accumulates rainwater and detritus, the decomposition of which sustains rich food
webs that can be conveniently surveyed in replicates (see the photo, left). Using
DNA sequencing, I estimated the species composition of the microbial communities as
well as the abundances of various pathways encoded in the microbial genomes. I
discovered that each bromeliad hosted a distinct community of microbial species (see
the figure, middle). Notably, less than 3% of the microbial species encountered in
the study were present in all bromeliads.

In contrast, microbial communities showed a striking similarity in terms of the
abundance of genes involved in various pathways, including those involved in
fermentation, oxygen respiration, and carbon fixation (see the figure, right). This
suggested that environmental constraints largely determined the growth of these
pathways and had much less influence over which species happened to represent each
pathway in a bromeliad, consistent with a pathway-centric paradigm.

Sequencing the Ocean Microbiome

To test the generality of my findings, I analyzed DNA sequencing data from an
international ocean microbiome survey (5), in combination with oceanographic data from
satellite imaging. Through extensive search of the literature, I classified over
30,000 marine microorganisms into various metabolic groups based on the pathways
that they use to gain energy (6). For example, I distinguished between organisms that
consume methane (a potent greenhouse gas) and organisms that eat sulfide (a toxic
gas found in parts of the ocean).

Using statistical methods, I discovered that environmental conditions strongly
predicted the distribution of metabolic groups across the world's oceans. In
contrast, environmental conditions poorly predicted which microbial species were
associated with each metabolic group in each location. This finding was perplexing,
because ocean currents can transport microorganisms across large distances, and yet
the same pathways were represented by different organisms in different locations of
the ocean. Hence, mechanisms other than environmental selection and limitation of
dispersal seem to influence which species get to perform these pathways in each
location.

Simulating Species' Stability

To find out what these mechanisms may be, I borrowed statistical tools from animal
ecology. I found that both in bromeliads (3) and in the ocean (6), the variation in species composition within
each metabolic group was likely driven by complex interactions between organisms.
Using computer simulations, I further demonstrated that such interactions—for
example, predation of bacteria by viruses—could indeed cause fluctuations in
species composition, even if the overall activity of metabolic pathways at the
community level is constant (7, 8, 9). This realization has important implications for
microbially catalyzed industrial processes, such as bioremediation of acid mine
drainage, where a stable microbial community is often an objective of operation
control. My findings suggest that taxonomic stability is neither easily achievable
through control of the operating environment alone nor a prerequisite for bioprocess
stability.

A Gene-Centric Model of Biogeochemistry Emerges

If the dynamics of individual genes become decoupled from particular species
assemblages, then we may be able to directly model the dynamics of these genes
within an ecosystem. Motivated by my previous findings, I developed a gene-centric
mathematical model for the biogeochemistry in Saanich Inlet, a fjord off Vancouver
Island (10). In Saanich
Inlet, annual oxygen depletion leads to dramatic shifts in microbially mediated
biochemical fluxes, and much research on ocean biochemistry uses Saanich Inlet as a
model ecosystem.

My model integrated DNA, RNA, and protein sequence data, as well as chemical
measurements, into a single framework. Using this model, I found that genes indeed
displayed population dynamics that resembled self-replicating organisms that are
feeding on each other's metabolic waste products. The model also revealed an
important and previously unsuspected microbial process that removes toxic sulfide
and transforms ammonia into nitrogen gas, with potentially strong implications for
ocean productivity.

In conclusion, environmental conditions appear to be directly coupled to the dynamics
of certain energy-transducing microbial pathways, whereas complex species
interactions influence which taxa get to perform each pathway. Disentangling the
pathway structure of microbial communities from their taxonomic structure, as
advanced by my work (4, 6, 10), will be an important component of future
research in microbial ecology.

As an undergraduate, Stilianos Louca studied physics and mathematics at the
Friedrich-Schiller-Universität, Germany, before going on to attain a Ph.D. in
applied mathematics at the University of British Columbia, Canada. During his
doctoral research, he investigated how microorganisms, in particular their genes,
interact with the environment and with each other to drive elemental fluxes at
ecosystem scales. Louca is currently a postdoctoral researcher at the Biodiversity
Research Centre in Vancouver, where he continues to investigate the ecology and
evolution of microbial metabolism using mathematical modeling, molecular sequencing,
and laboratory experiments. www.sciencemag.org/content/358/6368/1264

Jared Mayers is a resident in internal medicine at Brigham and Women's Hospital
in Boston, MA, working toward a career that balances basic science research with
clinical practice. After completing his undergraduate degree at Williams College, he
earned an M.D. from Harvard Medical School and a Ph.D. in biology from the
Massachusetts Institute of Technology. His research interests center on identifying
and understanding the mechanisms driving whole-body metabolic alterations and tissue
interactions in early disease states. Outside of the hospital and lab, he enjoys
running and spending time with his family. www.sciencemag.org/content/358/6368/1265.1

Kelley Harris studied mathematics as an undergraduate at Harvard and transitioned
into genomics during a postgraduate year at the Wellcome Trust Sanger Institute. She
then earned a Ph.D. in mathematics at University of California, Berkeley, with a
designated emphasis in computational biology, where she continued building
statistical methods that describe how genome sequences evolve. In January 2018,
Harris will finish her postdoctoral fellowship at Stanford and will become an
assistant professor of genome sciences at the University of Washington. www.sciencemag.org/content/358/6368/1265.2

A native of Europe, Mijo Simunovic sought higher education in the United States and
in France, earning a Ph.D. in theoretical chemistry from The University of Chicago
and a Ph.D. in experimental physics from the University of Paris. In his scientific
work, he pursues complex biological problems that are fundamentally driven by
physics. Currently, he is at The Rockefeller University where, as a junior fellow of
the Simons Society, he uses stem cells to build experimental models of the human
embryo, aimed at elucidating the earliest events in human development. Simunovic is
passionate about teaching, having served as a teaching consultant at the University
of Chicago and instructed undergraduate biophysics courses in Chicago and New York.
www.sciencemag.org/content/358/6368/1265.3